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Genetic Algorithms

89f010240c73a5bd5fbfed16788e162e

Introduction

This first semester subject ties directly with ......

Requirements

This subject must be coursed jointly with the subject of Fuzzy Logic in order to complete the optional field on Knowledge Analysis

Learning outcomes

  1. Know, understand, analyze and implement methods of evolutionary programming.
  2. Know, understand, analyze and apply genetic algorithms.
  3. Know and apply genetic algorithms library.
  4. Know, understand, analyze and apply different variants of genetic algorithms.

Teachers:

  • Alma Gómez Rodríguez (alma@uvigo.es)

Invited Speakers:

  • Pedro Villar Castro (pvillarc@ugr.es)
  • Ana Mª Sánchez López

Course Contents

  1. Introduction to Evolutionary Computation
  2. Genetic Algorithm

    • Basic Concepts
    • Diversity and Convergence
    • Multiple Solutions in Multimodal Problems
  3. Evolution Strategies
  4. Evolutionary Programming
  5. Algorithm Based on Differential Evolution (Differential Evolution - DE)
  6. Models of Evolution Based on Estimation of Distributions (EDA)
  7. Memetic algorithms
  8. Evolutionary Algorithms for Multiobjective Problems
  9. Genetic Programming
  10. Models Evolutionary Learning

Course Activities

  1. Classroom Lessons (2 ECTS).- It will consist mainly on magistral sessions and readings to introduce the work to be done in the other activities.
  2. Experiments and Practices (1 ECTS).- It will consist on the develop of little examples and exercises supervised by the teachers.
  3. Seminars (2 ECTS).- It will consist mainly in the presentation of a concrete item by students in small groups.
  4. Conferences (0,5 ECTS).- It will consist on the elaboration of an original scientific article where a practical application of the information theory is explained, and its oral exposition.
  5. Tutorials (0,5 ECTS).- It will consist in the solution of some problems proposed by the teachers, and the pursuit of the seminars and conferences.

Course Assessment

Evaluation Procedure for Regular-ASSISTANTS

  1. Theoretical Exposure Assessment of different jobs over the course that will demonstrate the acquisition of skills and basic knowledge, both theoretical and practical for the subject.
  2. Regular Attendance and active participation in classroom lessons and seminars. Active participation  means answer proposed questions by the teacher.
  3. Performing the practice exercises.
  4. Conducting seminar includes the development of a theme, its oral, exercise approach to colleagues and their evaluation.

Evaluation Procedure for NON-ASSISTANTS

  1. Presentation of a paper or technical report raised about the content of the subject
  2. Presentation of an application that solves a practical problem proposed.
  3. Oral presentation on the seminar on the topic that was assigned and on which it must have been from some basic references. Previously, shall submit a summary and a copy of the written submission prior to its assessment.
89f010240c73a5bd5fbfed16788e162e